环境保护署（EPA）动态缩小集成（EDDE）版本2：用于预测未来极端天气事件的基于3D物理的数据集

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-09-18 DOI:10.1016/j.dib.2025.112070

Megan S. Mallard , Tanya L. Spero , Jared H. Bowden , Jeff Willison , Kathy Brehme , Lara J. Reynolds

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引用次数: 0

摘要

美国环境保护署（EPA）动态缩小集成版本2 （EDDEv2）包含基于3D物理的未来条件和极端事件预测，网格间距为12公里，覆盖了北美大部分地区，重点是美国（CONUS）。天气研究与预报（WRF）模式用于在多种共享社会经济路径下缩小耦合模式比对项目第6阶段（CMIP6） 30年历史时期（1985-2014年）和75年未来时期（2025-2099年）的全球预估。WRF的输出被进一步处理，以创建符合气候和预报系统（CF）标准的自描述netCDF文件。EDDEv2数据的一个子集可以通过亚马逊网络服务（AWS）开放数据项目免费输出，时间频率从5分钟到每月不等。除了降水和2米温度等关键变量外，EDDEv2还包含其他动态一致的大气和土壤场，可以支持后续的建模应用，包括湿度、风、辐射变量、热通量、土壤温度和湿度等。到本世纪末的连续高频数据使EDDEv2非常适合探索可能在一系列时间尺度上发生的局部极端事件的潜在变化，包括极端高温和洪水。大量变量的使用有助于对农业、基础设施和生态系统以及其他应用程序的潜在影响进行建模。

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The Environmental Protection Agency (EPA) Dynamically Downscaled Ensemble (EDDE) version 2: A 3D physics-based dataset for projections of future extreme weather events

The U.S. Environmental Protection Agency (EPA) Dynamically Downscaled Ensemble version 2 (EDDEv2) contains 3D physics-based projections of future conditions and extreme events over a model domain with 12-km grid spacing covering most of North America and focusing on the contiguous U.S. (CONUS). The Weather Research and Forecasting (WRF) model is used to downscale global projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over a 30-year historical period (1985–2014) and a 75-year future period (2025–2099) under multiple Shared Socioeconomic Pathways. The output from WRF is further processed to create self-describing netCDF files conforming to the Climate and Forecasting System (CF) standards. A subset of EDDEv2 data is available with free egress via Amazon Web Services (AWS) Open Data Project at temporal frequencies ranging from 5 min to monthly. In addition to key variables like precipitation and 2-m temperature, EDDEv2 also contains other dynamically consistent atmospheric and soil fields that can support subsequent modeling applications, including humidity, winds, radiative variables, heat fluxes, and soil temperature and moisture, among others. The continuous, high-frequency data through the end of the century make EDDEv2 well-suited to explore potential changes to localized extreme events that can occur over a range of timescales, including heat extremes and flooding. The use of a large suite of variables facilitates modeling potential impacts on agriculture, infrastructure, and ecosystems, among other applications.

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

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